• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.197-201
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• 2018

인공위성 기반의 원격탐사자료는 홍수, 가뭄 등 자연재해에 대한 모니터링 및 예측에 활용되어 왔으며, 특히 인공위성을 이용한 광역적 강수량 추정 자료는 지형적 제약을 받는 지상관측자료와 비교하여 시공간적으로 연속적이고 균질한 강수량 자료 취득이 가능하다는 장점이 있다. 우리나라의 경우 상대적으로 조밀한 지상관측망이 구축되어 있어 공간적으로 상세한 강수량 정보를 생산할 수 있는 여건을 갖추고 있지만, 북한 지역의 경우 기상, 수문, 통계자료에 관한 자료의 접근 및 품질의 제한성으로 인해 미계측 지역에 대한 강수량의 추정에 한계가 있다. CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) 데이터는 1999년부터 미국국제개발처 (U.S. Agency for International Development, USAID), 미국항공우주국 (National Aeronautics and Space Administration, NASA), 미국해양대기청 (National Oceanic and Atmospheric Administration, NOAA)의 지원으로 개발된 전지구 강우데이터 자료이다. CHIRPS는 1981년부터 현재까지 전지구 강우자료를 0.05도 격자 해상도로 제공하고 있으며, 강수량의 추세 분석 및 가뭄 모니터링을 위해 활용되고 있다. 본 연구에서는 CHG (Climate Hazards Group)에서 제공하고 있는 인공위성을 이용한 광역적 강수량 추정 자료인 CHIRPS와 남한 및 북한의 지상관측 강수량 자료와의 비교를 통해 위성으로부터 유도된 격자 강수량자료의 정확도 및 지역적인 강수추정의 불확실성을 평가하고, 수자원 및 재해 분야 이용 가능성을 검토하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.162-162
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• 2023

Climate change is a complex phenomenon having its impact on diverse sectors. Temperature and precipitation are two of the most fundamental variables used to characterize climate, and changes in these variables can have significant impacts on ecosystems, agriculture, and human societies. This study evaluated the historical (1981-2010) and future (2011-2100) climatic trends in the Seti-Gandaki basin of Nepal based on 5 km resolution Multi Model Ensemble (MME) of 18 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for SSP1-2.6, SSP2-4.5 and SSP5-85 scenarios. For this study, ERA5 reanalysis dataset is used for historical reference dataset instead of observation dataset due to a lack of good observation data in the study area. Results show that the basin has experienced continuous warming and an increased precipitation pattern in the historical period, and this rising trend is projected to be more prominent in the future. The Seti basin hosts 13 operational hydropower projects of different sizes, with 10 more planned by the government. Consequently, the findings of this study could be leveraged to design adaptation measures for existing hydropower schemes and provide a framework for policymakers to formulate climate change policies in the region. Furthermore, the methodology employed in this research could be replicated in other parts of the country to generate precise climate projections and offer guidance to policymakers in devising sustainable development plans for sectors like irrigation and hydropower.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.367-367
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• 2021

최근 기후변화로 인해 극한 강우 사상의 빈도가 잦아짐에 따라 수공 구조물의 안전성이 저해되거나 인명 및 재산 피해가 발생할 가능성이 커지고 있다. 기후변화에 따른 기상현상의 변화 추세를 파악하고 대비하기 위해 CMIP (Coupled Model Intercomparison Project Phase)의 GCM(General Circulation Model) 기상자료 산출물이 활발하게 이용되고 있다. 기후변화 시나리오는 홍수기 방재 대책 수립 등의 연구에도 적용되고 있으나, GCM에서 산출된 기상자료의 시간 간격은 24시간 혹은 3시간 정도로 시간적 해상도가 낮아 홍수 모형의 입력자료로 사용되기 어려운 형태를 가지고 있다. 따라서 기후변화 시나리오를 홍수 모의 등의 분야에 접목하기 위해서는 GCM 자료의 시간적 해상도를 1시간 이하로 낮춤으로써 시나리오 산출물이 홍수모형과 적절하게 연결될 수 있도록 해야 한다. MRC (Multiplicative Random Cascade) 모형은 국내외에서 예보강우의 시간 분해 및 일강우 데이터 분해 연구에 활용된 바 있으며 관측 강우에 대하여 분해 성능이 준수함이 확인되었다. 이에 본 연구에서는 MRC 모형을 활용하여 미래 기후변화 시나리오 산출물에 적용함으로써 MRC 모형이 일단위 및 3시간 단위 기후변화 자료의 시간 분해에 대해 적절한 성능을 수행하는지 여부를 분석하고, 기후변화 자료의 최소 시간 간격별 강우 분해 결과를 비교·분석하고자 하였다. 본 연구의 결과는 향후 기후변화 시나리오 기반 기상자료 시간 분해에 대한 MRC 모형의 적용성을 평가하는 기초 자료로 활용될 수 있을 것으로 사료된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.305-305
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• 2022

A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.39-50
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• 2019

This study aims to assess the influence of climate change on the hydrological cycle at a basin level in North Korea. The selected model for this study is MRI-CGCM 3, the one used for the Coupled Model Intercomparison Project Phase 5 (CMIP5). Moreover, this study adopted the Spatial Disaggregation-Quantile Delta Mapping (SDQDM), which is one of the stochastic downscaling techniques, to conduct the bias correction for climate change scenarios. The comparison between the preapplication and postapplication of the SDQDM supported the study's review on the technique's validity. In addition, as this study determined the influence of climate change on the hydrological cycle, it also observed the runoff in North Korea. In predicting such influence, parameters of a runoff model used for the analysis should be optimized. However, North Korea is classified as an ungauged region for its political characteristics, and it was difficult to collect the country's runoff observation data. Hence, the study selected 16 basins with secured high-quality runoff data, and the M-RAT model's optimized parameters were calculated. The study also analyzed the correlation among variables for basin characteristics to consider multicollinearity. Then, based on a phased regression analysis, the study developed an equation to calculate parameters for ungauged basin areas. To verify the equation, the study assumed the Osipcheon River, Namdaecheon Stream, Yongdang Reservoir, and Yonggang Stream as ungauged basin areas and conducted cross-validation. As a result, for all the four basin areas, high efficiency was confirmed with the efficiency coefficients of 0.8 or higher. The study used climate change scenarios and parameters of the estimated runoff model to assess the changes in hydrological cycle processes at a basin level from climate change in the Amnokgang River of North Korea. The results showed that climate change would lead to an increase in precipitation, and the corresponding rise in temperature is predicted to cause elevating evapotranspiration. However, it was found that the storage capacity in the basin decreased. The result of the analysis on flow duration indicated a decrease in flow on the 95th day; an increase in the drought flow during the periods of Future 1 and Future 2; and an increase in both flows for the period of Future 3.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.629-642
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• 2018

Future variability of the spatial patterns of rainfall events is the point of water-related risks and impacts of climate change. Recent related researches are mostly conducted based on the outcomes from General Circulation Models (GCMs), especially Coupled Model Intercomparison Project, phase 5 (CMIP5) GCMs which are the most advanced version of climate modeling system. GCM data have been widely used for various studies as the data utility keep getting improved. Meanwhile the model performances especially for raw GCM outputs are rarely evaluated prior to the applications although the process would essential for reasonable use of model forecasts. This study attempt to quantitatively evaluate the skills of 29 CMIP5 GCMs in reproducing spatial climatologies of precipitation in East Asia. We used 3 different gridded observational data as the references available over the study area and calculated correlation and errors of spatial patterns simulated by GCMs. As a result, the study presented diversity of the GCM evaluation in the performance, rank, or accuracy by different configurations, such as target area, evaluation method, and observation data. Yet, we found that Hadley-centre affiliated models comparatively performs better for the meso-scale area in East Asia and MPI_ESM_MR and CMCC family showed better performance specifically for the korean peninsula. We expect that the results and thoughts of this study would be considered in screening suitable GCMs for specific area, and finally contribute to extensive utilization of the results from climate change related researches.

• Journal of Korea Water Resources Association
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• v.47 no.8
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• pp.671-684
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• 2014

Change point analysis is a efficient tool to understand the fundamental information in hydro-meteorological data such as rainfall, discharge, temperature etc. Especially, this fundamental information to change points to future rainfall data identified by reasonable detection skills can affect the prediction of flood and drought occurrence because well detected change points provide a key to resolve the non-stationary or inhomogeneous problem by climate change. Therefore, in this study, the comparative study to assess the performance of the 3 change point detection skills, cumulative sum (CUSUM) method, Bayesian change point (BCP) method, and segmentation by dynamic programming (DP) was performed. After assessment of the performance of the proposed detection skills using the 3 types of the synthetic series, the 2 reasonable detection skills were applied to the observed and future rainfall data at the 5 rainfall gauges in South Korea. Finally, it was suggested that BCP (with 0.9 posterior probability) could be best detection skill and DP could be reasonably recommended through the comparative study. Also it was suggested that BCP (with 0.9 posterior probability) and DP detection skills to find some change points could be reasonable at the North-eastern part in South Korea. In future, the results in this study can be efficiently used to resolve the non-stationary problems in hydrological modeling considering inhomogeneity or nonstationarity.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.79-87
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• 2017

The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.1-16
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• 2021

Global warming due to climate change is expected to significantly affect the hydrological cycle of agriculture. Therefore, in order to predict the magnitude of climate impact on agricultural water resources in the future, it is necessary to estimate the water demand for irrigation as the climate change. This study aimed at evaluating the future changes in water demand for irrigation under two Shared Socioeconomic Pathways (SSPs) (SSP2-4.5 and SSP5-8.5) scenarios for paddy rice in Gimje, South Korea. The APEX-Paddy model developed for the simulation of paddy environment was used. The model was calibrated and validated using the H₂O flux observation data by the eddy covariance system installed at the field. Sixteen General Circulation Models (GCMs) collected from the Climate Model Intercomparison Project phase 6 (CMIP6) and downscaled using Simple Quantile Mapping (SQM) were used. The future climate data obtained were subjected to APEX-Paddy model simulation to evaluate the future water demand for irrigation at the paddy field. Changes in water demand for irrigation were evaluated for Near-future-NF (2011-2040), Mid-future-MF (2041-2070), and Far-future-FF (2071-2100) by comparing with historical data (1981-2010). The result revealed that, water demand for irrigation would increase by 2.3%, 4.8%, and 7.5% for NF, MF and FF respectively under SSP2-4.5 as compared to the historical demand. Under SSP5-8.5, the water demand for irrigation will worsen by 1.6%, 5.7%, 9.7%, for NF, MF and FF respectively. The increasing water demand for irrigating paddy field into the future is due to increasing evapotranspiration resulting from rising daily mean temperatures and solar radiation under the changing climate.

• Atmosphere
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• v.26 no.2
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• pp.347-356
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• 2016

Radiosonde is an observation equipment that measures pressure (geopotential height), temperature, relative humidity and wind by being launched up from the ground. Radiosonde data which serves as an important element of weather forecast and research often causes a bias in a model output due to accuracy and sensitivity between the different manufacturers. Although Korean Meteorological Administration (KMA) and several institutes have conducted routine and intensive radiosonde observations, very few studies have been done before on the characteristics of radiosonde performance. Analyzing radiosonde observation data without proper understanding of the unique nature of those sensors may lead to a significant bias in the analysis of results. To evaluate performance and reliability of radiosonde, we analyzed the differences between two sensors made by the different manufacturers, which have been used in the campaign of Experiment on Snow Storm At Yeongdong (ESSAY). We improved a couple of methods to launch the balloon being attached with the sensors. Further we examined cloud-layer impacts on temperature and humidity differences for the analysis of both sensors' performance among various weather conditions, and also compared daytime and nighttime profiles to understand temporal dependence of meteorological sensors. The overall results showed that there are small but consistent biases in both temperature and humidity between different manufactured sensors, which could eventually secure reliable precisions of both sensors, irrespective of accuracy. This study would contribute to an improved sounding of atmospheric vertical states through development and improvement of the meteorological sensors.